The rise of large language models (LLMs) like ChatGPT has thrust generative artificial intelligence (AI) into the driver’s seat of retail technologies, prompting brands across industry subsegments to reassess their strategies. This development follows retailers’ years-long efforts to leverage AI’s earlier iterations to support novel customer experience initiatives. However, the latest applications of the technology come with some significant caveats.
Generative AI can foster fraud, for example, not infrequently in the form of customer impersonations or fake websites, highlighting the need for greater consumer and retailer vigilance in the age of AI. As the technology improves the precision of retail marketing and sales initiatives, stakeholders should embrace its transformative power with caution. Likewise, regulators should refine their responses to its application to advance the retail technology stack in tandem with consumer protections.
The marketing and sales functions are leading generative AI efforts at 16% of consumer and retail companies, with 57% of marketing and sales teams actively pursuing generative AI initiatives compared to just 31% of departments in other industries. However, the integration of generative AI into the retail technology stack for most businesses represents a complex set of challenges.
For retailers grappling with the promise of generative AI, perhaps the most prominent challenge they face is a simple, albeit difficult, one: contending with the industry’s shortage of skilled developer talent. Retailers will need to overcome this deficit to effectively implement and manage the technology across various business applications. AI’s intelligence may be artificial, but its development is anything but. Hence, retailers must invest in training and hiring for the right AI expertise, which can become time-consuming and costly. For most retailers, though, the rewards are worth the trouble, as generative AI could boost the consumer packaged goods (CPG) industry’s productivity by up to 2% of annual revenues, or an extra $660 billion.
The advent of AI and machine learning (ML), exemplified by platforms like ChatGPT, has spurred a new era in retail personalization. More than 90% of companies now use AI to automate personalization efforts and deliver real-time, tailored customer experiences. While AI offers significant advantages in this way, businesses must ensure that their models align with customer preferences and values, emphasizing the critical importance of harmonizing technology capability and ethical responsibility.
Consumers’ cautious embrace of AI-powered personalization in retail offers a similarly nuanced picture. While 41% of consumers feel fully comfortable with AI personalizing their experiences, the wider discomfort highlights an opportunity for retailers to offer greater transparency by educating their customers about how AI is utilized in creating personalized experiences. This puts the onus on retailers to do more to consider consumer boundaries and preferences, ensuring trust and alignment with customer values in their AI personalization strategies.
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